基于文本挖掘的地铁施工安全风险事故致险因素分析  

Analysis of Safety Risk Factors for Metro Construction Based on Text Mining Method

作　　者：李解[1] 王建平[1] 许娜[1] 周哲 

机构地区：[1]中国矿业大学力学与建筑工程学院,江苏徐州221116 [2]中建南方投资有限公司,广东深圳518000

出　　处：《隧道建设》2017年第2期160-166,共7页Tunnel Construction

基　　金：住建部科学技术研究项目(2015-R3-010)

摘　　要：地铁工程项目是典型的高风险大型复杂项目,施工安全风险事故多发且引发因素众多。为明确施工过程中存在的致险因素,为安全风险事故的预控提供依据,选取2002—2015年国内151例地铁施工安全风险事故报告,借助R语言和文本挖掘的方法,分别对事故报告进行分词处理、特征项选择、向量空间模型构建、共现规律识别,并利用词云和网络结构图等方法可视化文本挖掘结果;从中发现地铁施工安全风险事故的6项关键致险因素和23项一般致险因素,并以关键致险因素为基础构建致险因素集合,为地铁施工安全风险事故的预控提供参考。The Metro engineering projects are typically high risky and complex,of which the safety accidents occur often and the risk factor varies. 151 Metro construction safety accident reports from 2002 to 2015 are selected to identify the risk factors and provide reference for risk control. Word processing,feature selection,vector space model and cooccurrence pattern recognition are carried out for risk accident reports based on R language and text mining method; the word cloud and network structure are used to visualize text mining results. Finally,6 key risk factors and 23 general risk factors are identified; and a risk factor set is built based on key risk factors. The results can provide reference for safety risk control of Metro construction.

关 键 词：地铁施工 安全风险事故 文本挖掘 R语言 致险因素 

分 类 号：U45[建筑科学—桥梁与隧道工程]